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Aim/Purpose: This study was aimed at enhancing students’ learning of software engineering methods. A collaboration between the Computer Science, Business Management, and Product Design programs was formed to work on actual projects with real clients. This interdisciplinary form of collaboration simulates the realities of a diverse Software Engineering team. Background: A collaborative approach implemented through projects has been the established pedagogy for introducing the Software Engineering course to undergraduate Computer Science students. The collaboration, however, is limited to collaboration among Computer Science students and their clients. This case study explored an enhancement to the collaborative approach to project development by integrating other related disciplines into the project development framework; hence, the Interdisciplinary Approach. Methodology: This study adopted the case method approach. An interdisciplinary service innovation activity was proposed to invite other disciplines in the learning process of the computer science students. The agile methodology Scrum was used as the software development approach during project development. Survey data were collected from the students to establish (a) their perception of the interdisciplinary approach to project development; (b) the factors that influenced success or failure of their team to deliver the project; and (c) the perceived skills or knowledge that they acquired from the interdisciplinary approach. Analysis of data followed a mixed method approach. Contribution: The study improved the current pedagogy for Software Engineering education by integrating other related disciplines into the software project development framework. Findings: Data collected showed that the students generally accepted the interdisciplinary approach to project development. Factors such as project relevance, teamwork, time and schedule, and administration support, among others, affect team performance towards project completion. In the case of the Computer Science students, results show that students have learned skills during the experience that, as literature reveal, can only be acquired or mastered in their future profession as software engineers. Recommendations for Practitioners: The active collaboration of the industry with the University and the involvement of the other related courses in teaching software engineering methods are critical to the development of the students, not only in learning the methodology but also as a working professional. Recommendation for Researchers: It is interesting to know and eventually understand the interactions between interdisciplinary team members in the conduct of Software Engineering practices while working on their projects. More specifically, what creative tensions arise and how do the interdisciplinary teams handle the discourse? Impact on Society: This study bridges the gap between how Software Engineering is taught in the university and how Software Engineering teams work in real life. Future Research: Future research is targeted at refining and elaborating the elements of the interdisciplinary framework presented in this paper towards an integrated course module for Software Engineering education.

Abstract. Fire disasters are common occurrences in the urban settlements of the Philippines. Concerned agencies like the Bureau of Fire Protection (BFP) and the Disaster and Risk Reduction Management Office (DRRMO) are constantly planning ways to prevent and mitigate fire disasters. The key to an effective plan against fire disaster is understanding how a potential fire can spread in a community. By combining both GIS and Probabilistic Cellular Automata (PCA), this paper solves the task of fire spread modeling and simulation. PCA is a model that consists of a regular grid of cells, whose cells are updated according to rules that take into account both the cell’s current state and the cell’s neighbors’ states. The model we developed factors in wind, building materials, and building density. The model was designed after several fires in major cities of Cebu, Philippines. An accuracy of 83.54% and a Cohen’s Kappa coefficient of 0.67 was achieved. Further, a web-based tool was developed to aid in fire disaster planning.

Abstract. Urban fire continues to be a persistent disaster, especially with the proliferation of highly dense urban settlements. As a response, several measures were established to help mitigate the losses caused by fire including simulating the fire spread. The cellular automaton system has been widely used to simulate the complex process of fire development along with Physics-based models. A data-driven approach has been rarely employed. This paper presents the result of incorporating machine learning techniques to the existing cellular automaton based urban fire spread models. Specifically, instead of manually calculating the ignition probability of each cell in the automaton, the Extreme Learning Machine (ELM) was used to learn the ignition probability from the historical data. After building the model, its performance was evaluated using the data collected from the four fires in Basak, Lapu-Lapu City. By using a confusion matrix to compare the actual and the predicted values, the Burned Actual – Burned Predicted relationship was derived. Results suggest that the proposed method can effectively describe the development of fire, and the model accuracy is quite good (i.e., the Burned Actual - Burned Predicted relationship ranges from 78% to 83%). Lastly, the study was able to demonstrate the possibility of using a data-driven approach in creating a simple cellular automaton fire spread simulation model for urban areas. Further studies utilizing more fire incident data on with varying properties is recommended.